株式会社極東書店トップ商品一覧Mathematical Modeling and Optimization : An Essay for the Design of Computer-Based Modeling Tools. Softcover reprint of the original 1st ed. 1999.

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Mathematical Modeling and Optimization

Mathematical Modeling and Optimization : An Essay for the Design of Computer-Based Modeling Tools. Softcover reprint of the original 1st ed. 1999.

・ISBN 978-1-4419-4814-4 paper EUR 99.99

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お気に入り
著者・編者Huerlimann, Tony,
シリーズApplied Optimization
出版社(Springer-Verlag New York Inc., US)
出版年月2013
ページ数313 pp.
言語ENG
ニュース番号<M25-23733>

解説

Computer-based mathematical modeling - the technique of representing and managing models in machine-readable form - is still in its infancy despite the many powerful mathematical software packages already available which can solve astonishingly complex and large models. On the one hand, using mathematical and logical notation, we can formulate models which cannot be solved by any computer in reasonable time - or which cannot even be solved by any method. On the other hand, we can solve certain classes of much larger models than we can practically handle and manipulate without heavy programming. This is especially true in operations research where it is common to solve models with many thousands of variables. Even today, there are no general modeling tools that accompany the whole modeling process from start to finish, that is to say, from model creation to report writing. This book proposes a framework for computer-based modeling. More precisely, it puts forward a modeling language as a kernel representation for mathematical models. It presents a general specification for modeling tools. The book does not expose any solution methods or algorithms which may be useful in solving models, neither is it a treatise on how to build them. No help is intended here for the modeler by giving practical modeling exercises, although several models will be presented in order to illustrate the framework. Nevertheless, a short introduction to the modeling process is given in order to expound the necessary background for the proposed modeling framework.